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. 2022 Dec 7;42(3):2279–2293. doi: 10.1007/s12144-022-04041-7

Modeling the contributions of EFL university professors’ emotion regulation to self-efficacy, work engagement, and anger

Ehsan Namaziandost 1,✉, Tahereh Heydarnejad 2, Vahid Rahmani Doqaruni 2, Zeinab Azizi 3
PMCID: PMC9735219  PMID: 36531192

Abstract

As university professors’ emotion regulation (ER) plays a pivotal role in their efficacy, it is essential to explore if it is significantly correlated with work engagement (WE), self-efficacy, and anger at the workplace. To respond to the call, this research inspected the contributions of university professors’ ER to their WE, self-efficacy, and anger. For this purpose, a total of 278 university professors were selected using a convenience sampling method and asked to fill out Language Teacher Emotion Regulation Inventory, Engaged Teacher Scale, Teacher Sense of Efficacy Scale, and Teacher Anger Scale. A structural equation modeling was used to analyze the gathered data. Results disclosed that the participants’ ER significantly contributed to their WE and self-efficacy. Additionally, the findings documented that the participants’ ER was negatively correlated with their anger. The implications of the findings are discussed for pertinent stakeholders.

Keywords: Anger, EFL university professors, Emotion regulation, Self-efficacy, Work engagement

Introduction

To have a true understanding of the role of emotions in second/foreign language (L2) teachers’ work, it is of utmost importance to find out why and how they make use of particular emotions in their classroom context with what intensity and quality. This is called emotion regulation (ER) and refers to “the set of processes whereby people manage all of their emotionally charged states, including specific emotions, affect, mood, and stress” (Koole, 2009, p. 29). ER is of particular importance in L2 classrooms where teachers constantly regulate their emotions due to various irritations and frustrations (Akbari et al., 2017; Morris & King, 2018). It seems that L2 teachers cannot create a friendly and productive learning context in their classrooms unless they can regulate their emotions, specifically the negative ones (Dewaele & Li, 2020). However, despite such an importance, empirical studies of ER are rare within L2 education (Morris & King, 2020). This is unfortunate as L2 teachers take several and various roles and responsibilities in their classrooms (O’Dwyer, 2006) which makes it unavoidable to experience specific subject-related emotions in unfamiliar emotional contexts. To make it even more complicated, it has been shown that some of these roles and responsibilities are culturally-informed (Mesquita et al., 2016).

On the other hand, studying different factors which might affect ER seems necessary due to the fact that it has been shown that emotions function on multi-dynamic levels (Fried et al., 2015; King & Ng, 2018). In other words, it has been proposed that emotions are continually shaped by contexts rather than being intrapersonal phenomena. In this way, different factors which might influence a teacher’s emotions range from personal experiences and relationships with students, colleagues and administrators to the immediate political, cultural and social contexts in which they work (Boiger & Mesquita, 2012). For example, a teacher might feel happy when a weak student eventually understands a difficult concept or gives the correct answer to a difficult question, disappointed when a colleague does not share their teaching experience, discouraged when the school principal does not care about their innovative practices in the classroom, frustrated when they are not allowed to express their ideology due to political restrictions, pleased when they see their teaching affects their students’ cultural awareness, and satisfied when they are respected in their community.

Given the pivotal role played by ER, this research aims to inspect its contributions to psycho-emotional constructs, such as work engagement (WE), self-efficacy, and anger. Put it more exactly, this research aimed to explore if EFL university professors’ ER is significantly correlated with their WE, self-efficacy, and anger. By disclosing such relationships, it is hoped that the findings of this research can be useful to help EFL university professors realize the power of emotions. That is, it is hoped that the findings of this research can further the understanding of EFL university professors regarding the contributions of their emotions to teaching profession and learning how to manage their emotions.

Literature review

Emotion regulation in L2 education

Given that effective educational systems are made by successful teachers, factors contributing to their professional success should be carefully studied. To give an appropriate response to this necessity, different factors, such as personal factors (Derakhshan et al., 2020; Fathi et al., 2021a, b), interpersonal factors (Nayernia et al., 2020; Pishghadam et al., 2021), and emotional factors (Fan & Wang, 2022; Namaziandost et al., 2022) should be studied. Previous research has shown that there is a mutual relationship between teachers’ professional success and well-being (Fan & Wang, 2022; Wong & Zhang, 2014). As put forward by Garg and Rastogi (2009), well-being deals with the status in which teachers are happy and satisfied in the classrooms.

Tamir (2016) posits that individuals regulate their emotions to achieve different goals, such as instrumental goals (i.e., performance and social), epistemic goals (i.e., an individual’s sense of self), and hedonic goals (i.e., psychological health). Previous research has shown that teachers apply ER to achieve the same goals as they manage their classrooms for instrumental purposes (Hosotani & Imai-Matsumura, 2011; Sutton, 2004; Yin & Lee, 2012), take teaching responsibilities for epistemic purposes (Hagenauer & Volet, 2014; Hosotani & Imai-Matsumura, 2011; Sutton, 2004; Yin & Lee, 2012), and show their well-being for hedonic purposes (Han & Wang, 2021; Haeussler, 2013). So, when a teacher decides to show their happiness to students, they are likely to create a positive atmosphere in the classroom (instrumental), or consider it as part of their job to make students feel happy (epistemic), or to feel pleasant emotions (hedonic).

Teachers use different strategies to modify their emotions so that they can actualize the educational purposes. Different taxonomies have been proposed to explain and rationalize these strategies. Gross’s (1998, 2015) ‘Process Model of Emotion Regulation’ is one of the often-cited models which has received considerable attention in recent years (e.g., Haeussler 2013; Jiang et al., 2016; Sutton, 2004). The model’s strength lies in its comprehensiveness as it helps to delve into ER from both external (i.e., environmental) and internal (i.e., cognitive) perspectives. This model proposes that emotions emerge along a timeline. When an individual encounters an emotional situation, their attention is provoked and they try to evaluate the situation. In case the emotional situation is considered important, five different types of strategies, including situation regulation, situation modification, attentional deployment, cognitive change, and response modulation might be used to regulate that particular emotion. The situation selection refers to an individual’s decision to engage in the desirable emotions or avoid undesirable emotions. The situation modification deals with an individual’s attempt to modify the emotional impact of a situation. The attentional deployment is concerned with controlling the amount of attention to alter an emotional response. The cognitive change means an individual’s attempt to change the evaluation of a situation to affect it emotional influence. The response modulation is viewed as an individual’s engagement in a behavior to affect the generated emotion.

A more recent ER model which has specifically been developed and validated for L2 teachers belongs to Heydarnejad et al. (2021). It is called Language Teacher Emotion Regulation Inventory (LTERI) and involves 27 items. According to the Heydarnejad et al. (2021), LTERI “categorizes language teacher emotion regulation strategies into six dimensions, namely, situation selection, situation modification, attention deployment, reappraisal, suppression, and seeking social support” (p. 12). They took the first three dimensions of the model (i.e., situation selection, situation modification, and attention deployment) from Gross’s (1998, 2015) Process Model of Emotion Regulation. Their fundamental meanings were offered above. Reappraisal refers to a teacher’s attempt to redirect attention to more pleasant situations. Suppression deals with a teacher’s attempt to suppress unpleasant emotions. Reappraisal and suppression were taken from the study of Gross and John (2003). Finally, seeking social support deals with a teachers’ intention to share problems with colleagues (Jennings & Greenberg, 2009; Taxer & Gross, 2018).

Self-efficacy in L2 education

One of psycho-emotional constructs receiving huge attention over the last decades is self-efficacy. It is viewed as an individual’s self-perception about their ability in organizing and executing particular tasks to achieve specific goals (Bandura, 1977). Concerning teachers, it refers to “teachers’ beliefs about their personal capabilities to perform their duties in the classroom” (Klassen et al., 2010, p. 466). It seems that teachers with high self-efficacy believe more in themselves and their professional capabilities. The concept of teacher self-efficacy has been characterized by some features in the classroom context. It is related to teacher’s judgment of their ability in handling the classroom, encouraging and involving students, and employing instructional strategies (Sarfo et al., 2015; Tschannen-Moran et al., 1998).

As self-efficacy plays a pivotal role in actualizing educational objectives by teachers, a mass of studies has explored it across the globe (e.g., Atay, 2007; Wyatt & Dikilitas, 2021; Zonoubi et al., 2017). Previous studies fall into two main bodies of research. The first category includes external and internal variables influencing teachers’ self-efficacy. Some of these factors entail teaching experience (e.g., Hoang & Wyatt, 2021), proficiency level (e.g., Choi & Lee, 2016; Wyatt & Dikilitas, 2021), professional development (e.g., Cabaroglu, 2014; Karimi, 2011; Lee & Davis, 2020; Zonoubi et al., 2017), mode of instructional delivery (e.g., Kissau & Algozzine, 2015), and practicum (e.g., Atay, 2007). The second category deals with the correlation between teachers’ self-efficacy and other psycho-emotional constructs, like emotional intelligence (e.g., Kostic-Bobanovic, 2020; Rastegar & Memarpour, 2009), teacher identity (e.g., Moslemi & Habibi, 2019), occupational commitment (e.g., Gilbert et al., 2014), job satisfaction (e.g., Davaribina & Ghobadi Asl, 2021; Safari et al., 2020), and teacher burnout (e.g., Akbari & Tavassoli, 2011; Davaribina & Ghobadi Asl, 2021; Khani & Mirzaee, 2015).

Although previous research has inspected L2 teachers’ self-efficacy from different perspectives, its correlation with ER has been overlooked in this strand of research. This importance arises from the fact that if we have a robust understanding of the correlation between teachers’ ER and their self-efficacy, we can examine if self-efficacious teachers can regulate their emotions when they encounter an emotionally challenging situation. In this way, gaining insight into this relationship will help teacher educators and administrators alike to foster the self-confidence of teachers at a pedagogical level by raising teachers’ awareness of such situations and look for specific patterns at a theoretical level.

Work engagement in L2 education

Despite the fact that teaching is considered a demanding job (McIntyre et al., 2017), many teachers are so passionate about their profession that they have devoted their whole life to the act of teaching. This is termed WE and refers to the “positive, fulfilling and work-related state of mind that is characterized by vigor, dedication and absorption dimensions” (Schaufeli et al., 2002, p. 75; emphasis added). The first dimension, namely vigor, means “high levels of energy and mental resilience while working, the willingness to invest effort in one’s work, and persistence also in the face of difficulties”, while the second dimension, namely dedication, refers to “a sense of significance, enthusiasm, inspiration, pride, and challenge”, and the third dimension, namely absorption, deals with “being fully concentrated and happily engrossed in one’s work, whereby time passes quickly and one has difficulties with detaching oneself from work” (Hakanen et al., 2006, pp. 498–499). Another model considered as the theoretical foundations of this research posits that work-engagement includes four different kinds of engagement, including cognitive, emotional, social, physical (Klassen et al., 2013). Cognitive engagement refers to the level of focused intensity, engrossment, and concentration devoted by teachers to their job duties (Huang et al., 2022; Rothbard, 2001). Emotional engagement deals with the level of joy that teachers experience in doing job duties (Russell & Barrett, 1999). Social engagement points to the time and energy devoted by teachers to establish long-term, meaningful connections with colleagues and students (Klassen et al., 2013). Physical engagement represents the time and energy that teachers put into accomplishing job duties.

Owing to the fact that the teachers who are more engaged with their job duties are more interested in what they do and have a more positive attitude toward their job, recently researchers’ attention has been drawn to the factors which might affect teachers’ WE in L2 education (e.g., Amini Faskhodi & Siyyari, 2018; Bao et al., 2021; Fathi et al., 2021a, b; Han & Wang, 2021). While few studies have inspected the effects of diverse factors on teachers’ WE in L2 education, ER as an important variable has received scant attention. Taking a careful look at the literature reveals that only one empirical study has been conducted on the contributions of ER to predicting L2 teachers’ WE. In a cross-cultural study, Greenier et al. (2021) explored the contributions of ER and psychological well-being to Iranian and British L2 teachers’ WE. Employing a sequential explanatory mixed-methods approach, they first distributed questionnaires among 255 Iranian and 108 British language teachers, and then conducted interviews with 6 Iranian and 5 British language teachers. Their findings disclosed that both the participants’ WE was positively correlated with their ER and psychological well-being. In addition, as the correlation between psychological well-being and WE was stronger among the British teachers, they concluded that the cross-cultural differences should be given enough attention. To increase the credibility of these findings, this research aimed to disclose the contributions of EFL university professors’ ER and WE.

Anger in L2 education

Emotions have recently become a central focus in L2 education (Bigelow, 2019). There are good reasons for this “affective turn” (Pavlenko, 2013) due to the effects of L2 teachers’ emotions on L2 learners’ achievement (Golombek & Doran, 2014), their burnout (Khajavy et al., 2017), and attrition (Wolf & De Costa, 2017). Therefore, a mass of studies has focused on L2 teachers’ emotional experiences by investigating some of the most common emotions, such as anxiety (e.g., Alrabai, 2015; Merc, 2011; Song, 2018), stress (e.g., Bress, 2006), and frustration (e.g., Cowie, 2011; Morris & King, 2018). Those studies have generally investigated the sources of L2 teachers’ emotions and the factors shaping their construction and expression.

Anger is considered as an unpleasant emotion in educational contexts (Keller et al., 2014; Sutton, 2007; Sutton & Wheatley, 2003). It has been of particular interest in L2 education. For example, using an appraisal-theoretical framework, Khajavy et al. (2018) examined the antecedents of EFL teachers’ pleasant and unpleasant emotions, including anger. The results of the semi-structured interviews with 11 teachers evidenced that disciplinary issues, lack of student commitment to their learning, and explaining a topic to students several times were the primary antecedents of the participants’ pleasant and unpleasant emotions. Adopting a critical approach to analyzing teachers’ emotions, Alzaanin (2021) delved into nine female EFL university professors’ emotional experiences. The results revealed that the construction, expression, and communication of teachers’ emotions were largely affected by the kind of relationships in the classroom and the institutional system. Additionally, they found that as the participants felt disempowered during the students’ disruptive behaviors and were constrained by institutional policies, they felt more anger. Despite such attempts to shed more light on anger as an important and common emotion in L2 classrooms, it seems that more studies are needed to gain a deeper insight into this particular emotion. Thus, this research purported to examine if EFL university professors’ ER significantly contributed to relieving their anger.

Related studies in the literature

The contributions of ER to teachers’ well-being have been explored in a range of studies. To pave the ground for the present study, some of them are critically reviewed. In a study, the effects of emotion regulatory strategies on university professors’ frustration were investigated by Morris and King (2018). Their results indicated that using the emotion regulatory strategies was so beneficial to promote their confidence in taking control of the unpleasant situations in their workplace. Moreover, Taxer and Gross (2018) inspected the cause and effect of ER. They found that the participants’ who had instrumental and hedonic emotional regulation purposes could better take control of their students’ emotions and their own one. Furthermore, their findings evidenced that teachers’ views toward emotional display rules in the classroom, their views toward ER strategies and burnout feelings were significantly correlated. They uncovered that the participants’ views toward emotional display rules in the classroom were positively correlated with views toward ER strategies and burnout feelings. Likewise, Fathi and Derakhshan (2019) explored the impact of Iranian EFL teachers’ self-efficacy and ER on teaching stress. They found that the EFL teachers’ self-efficacy and ER significantly affected their teaching stress. Plus, Fathi et al. (2021a, b) used a structural model to disclose the correlations between Iranian EFL teachers’ reflection, self-efficacy, burnout, and ER. Overall, their findings unveiled that ER mediated the correlations between teachers’ reflection, self-efficacy, and burnout. Namaziandost et al. (2022) examined the correlation between Iranian EFL teachers’ reflective teaching, ER, and immunity, as well as the linkage between their ER and immunity. A strong positive correlation was uncovered between the participants’ reflective teaching, ER, and immunity. Additionally, it was found that the participants’ ER was a strong determinant of their immunity. Moreover, the contributions of critical thinking and ER to university professors’ immunity were investigated by Li et al. (2022). Their results revealed that the participants’ ER was highly correlated with their critical thinking. Furthermore, it was found that the participants’ immunity was a strong predictor of their ER. Finally, Deng et al. (2022) conducted a study to reveal if EFL teachers’ ER was significantly correlated with their WE, self-efficacy, and anger. They discovered that the participants’ ER was positively correlated with their WE and self-efficacy and negatively linked with their anger at the workplace.

As it may be implied from the above-alluded studies, the contributions of EFL university professors’ ER to self-efficacy, WE, and anger has been left disregarded in the Iranian higher education context. As the higher education context is quite unique in Iran, it is essential to examine if EFL university professors’ ER significantly contribute to their self-efficacy, WE, and anger. Therefore, this research was to inspect if Iranian EFL university professors’ ER substantially contributed to their self-efficacy, WE, and anger. To shed light on the possible relationships between the above-mentioned teacher attributed constructs (ER, self-efficacy, WE, and anger), a model was proposed in the current research (Fig. 1). Then, this proposed model was tested via Structural Equation Modeling (SEM) employing Linear Structural Relation (LISREL) 8.80. The following research question was put forward to meet these purposes:

Fig. 1.

Fig. 1

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Theoretical structural equation model

  • RQ. Does EFL university professors’ ER significantly contribute to their self-efficacy, WE, and anger in the Iranian higher education context?

Consistent with the research question above, the null hypothesis below was formulated:

  • H01. EFL university professors’ ER does not significantly contribute to their self-efficacy, WE, and anger in the Iranian higher education context.

Theoretical model

This research rests on the premise that EFL university teachers’ ER contributes to their self-efficacy, WE, and anger. This is displayed in Fig. 1.

Method

Setting and participants

This research was conducted in Iranian state-run universities. The higher education system in Iran is administered through three kinds of universities: state-run, private (Azad), and distance-learning universities (Payame Noor). To study at state-run universities, candidates have to take a centralized examination (Kunkur) and gain a good rank. Studying at the state-run universities is free of charge for all students and they are directed and supervised by the Ministry of Science, Research and Technology. The university professors should be highly competent in terms of pedagogical and research issues to be accepted in the Iranian run-state universities.

The participants of this research consisted of 278 EFL university professors selected using a convenience sampling method. As stressed by Riazi (2016), it is a kind of non-probability sampling used to select a sample of participants for the population which is easy to reach. They included both males (n = 164) and females (n = 114), aged from 27 to 50 years old (M = 35.039, SD = 7.384), and their teaching experiences varied from 1 to 25 years (M = 9.082, SD = 7.322). They majored in English Teaching (n = 127), English Literature (n = 59), English Translation (n = 67), and also Linguistics (n = 25). To conduct this research, the researchers adopted a web-based platform started in March and ended in October 2021 to collect the required data. The researchers used it to send the questionnaires to the participants through Google Forms. It should be noted that the return rate was 71. 5% and no data were missed. Of particular note is that the electronic questionnaires were started with a written consent form. If they were willing to take part in the research, they had to sign the written consent to be directed to the questionnaires.

Instruments

The researchers used some instruments to gather the needed data. The first instrument included the Language Teacher Emotion Regulation Inventory (LTERI). It was designed and validated by Heydarnejad et al. (2021) and the researchers used it to measure the participants’ ER. The participants had to read a statement picturizing a situation which they may have encountered already at the workplace and rate the statements concerning their intended ER strategies. The instrument entailed 27 items on a five-point Likert scale, ranging from 1 (= never) to 5 (= always). It measures six factors, including situation selection (e.g., “I try to avoid discussing with troublesome parents”.), situation modification (e.g., “If my students make me angry in language classes, I try to advise them”.), attention deployment (e.g., “When I feel anxious in my language classes, I shift my attention to something pleasant”.), reappraisal (e.g., (“When I feel upset in my language classes, I redirect my attention to more pleasant matters”.), suppression (e.g., “If I feel anxious in my language classes, I try to suppress that”.), and seeking social support (e.g., “When I feel frustrated in my language classes, I share my troubles with my colleagues”.).

The second instrument adopted in this research was The Teachers’ Sense of Efficacy Scale (long form). It was designed and validated by Tschannen-Moran and Hoy (1998) and the researchers used it to gauge self-efficacy among the participants. It consists of 24 on a six-point Likert scale, ranging from 1 (= strongly disagree) to 9 (= strongly agree). It measures their kinds of efficacy, namely instructional strategies (“I know how to foster student creativity”.), students’ engagement (e.g., “I know how to craft good questions for my students”.), and classroom management (e.g., “I know how I should establish a classroom management system with each group of students”.).

The third instrument included the Engaged Teacher Scale (ETS). It was designed and validated by Klassen et al. (2013) and the researchers employed it to measure the participants’ WE. It comprises 16 items on a seven-point Likert scale 1 (= strongly disagree) to 7 (= strongly agree). It entails four factors representing the underlying dimensions of teachers’ WE: cognitive engagement (e.g., “While teaching, I get absorbed in my work”.), emotional engagement (e.g., “I really put my heart into teaching”.), social engagement: students (e.g., “I connect well with my students”.), as well as social engagement: colleagues (e.g., “I am accessible to my colleagues”.), and physical engagement (e.g., “I devote a lot of energy to teaching”.).

The last instrument was the Teacher Anger Scale. Designed and validated by Burić and Frenzel (2019), the researchers utilized it to measure the participants’ anger. It contains 16 items on a five-point Likert scale, ranging from 1 (= never) to 5 (= always). It assesses four dimensions, including: students-related (e.g., “The reactions of some students frustrate me so much that I would rather just quit the job”.), parents-related (e.g., “I feel resistance and anger with parents who overestimate their children’s real capabilities”.), colleagues-related (e.g., “I wish to yell when I just think about the improper behaviour of some colleagues”.), and system-related (e.g., “I get annoyed because educational regulations and laws are prescribed by people who have never worked in the school”.).

Prior to the main study, the researchers recruited an expert in translation to translate the questionnaires in the participants’ mother-tongue. Afterward, they administered them to a sample of 30 university professors to measure their reliability. The results of the internal-consistency calculated using Cronbach’s alpha yielded a range from 0.71 to 0.81 for the LTERI, from 0.74 to 0.86 for the TSES, from 0.71 to 0.82 for the ETS, and from 0.71 to 0.86 for the TAS, respectively. Then, using the experts’ judgment strategy, they invited two university professors majoring in Applied Linguistics to measure the validity of the instruments. After examining the instruments in terms of face and content validities, they affirmed that the instruments can be employed in the current study.

Data collection procedures

The researchers took some distinct steps to conduct this study. First, they recruited an expert translator to translate the questionnaires into Persian. Second, they administered them to a sample of 30 EFL university professors who were similar to the participants in the main study in terms of gender, major, and teaching experience to measure their reliability. Then, they invited two university professors at Applied Linguistics to check out if the instruments had the required validity. They offered some comments regarding the language and the content of the instruments. After applying the given comments by the researchers, the university professors approved that they enjoyed a high level of validity. Third, the researchers sent the questionnaires to the participants via Google Forms. The researchers were available on phone to respond to the participants’ questions concerning the content of the questionnaires. The participants’ responses were stored in a database.

Data analysis procedures

The researchers used different statistical procedures to analyze the collected data. They measured the reliability of the scales through Cronbach’s alpha formula. Furthermore, they assessed the normality distribution of the collected data via a Kolmogorov Smirnov Test. Having been assured of the normality assumption of the collected data, they analyzed them using a Confirmatory Factor Analysis (CFA) and a SEM using LISREL 8.80. An SEM model is built of sub-models, namely the measurement model and the structural model. The researchers used the measurement model to measure the correlations between the observed variables and latent variables. And, they used the structural model to gauge the correlations between the latent variables. Of particular note that the researchers validated the all latent variables using CFA prior to testing the structural model (Hair et al., 1998).

Results

In this section, the gained results are presented. Table 1 presents the calculated descriptive statistics gained for the participants’ emotion regulation, self-efficacy, WE, and anger.

Table 1.

Results of descriptive statistics for the Iranian EFL university professors’ ER, self-efficacy, WE, and anger

Inventory Subscale N Min Max Mean Std. Deviation
LTERI Situation Selection 287 1.000 5.000 3.973 0.806
Situation Modification 278 2.000 4.490 3.744 0.746
Attention Deployment 278 2.000 4.560 3.861 0.917
Reappraisal 278 1.000 4.000 3.868 0.728
Suppression 278 2.000 5.000 2.974 0.616
Seeking Social Support 278 2.750 5.000 3.896 0.617
TSES Student Engagement 278 2.750 8.625 6.213 0.727
Instructional Strategies 278 3.875 9.000 6.290 0.962
Classroom Management 278 4.375 9.000 6.272 0.981
ETS Cognitive Engagement 278 3.750 7.000 5.396 0.587
Emotional Engagement 278 3.250 7.000 5.321 0.762

Social Engagement: Students

Social Engagement: Colleagues

278

278

3.500

2.000

7.000

7.000

5.260

4.733

0.657

0.948
TAS Students-Related 278 2.000 4.250 3.339 0.599
Parents-Related 278 1.000 5.000 2.719 0.825
Colleagues-Related 278 1.000 4.250 2.933 0.915
System-Related 278 1.000 4.250 2.538 0.949
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As reported in Tables 1, concerning the dimensions of the participants’ ER, the situation selection (M = 3.973, SD = 0.806) and the seeking social support (M = 3.896, SD = 00.617) received the highest mean scores, while the suppression gained the lowest mean score (M = 2.974, SD = 0.616). Moreover, regarding the dimensions of self-efficacy, the instructional strategies gained the highest mean score (M = 6.290, SD = 0.962). Whereas the classroom the student engagement received the lowest mean score (M = 6.213, SD = 0.727). Additionally, considering teacher engagement, the mean score of cognitive engagement (M = 5.396, SD = 0.587) was the highest one among all the components. The mean scores of the subsequent sub-scales were as follows: the emotional engagement (M = 5.321, SD = 0.762), the social engagement: students (M = 5.260, SD = 0.657), and social engagement: colleagues (M = 4.733, SD = 0.948). Besides, regarding teacher anger’ subscales, student-related anger (M = 3.339, SD = 0.599) was the main cause of the EFL university professors’ anger at the workplace. Colleagues-related (M = 2.933, SD = 0.915), system-related (M = 2.538, SD = 2.538), and parents-related anger (M = 2.719, SD = 0.825) were the subsequent triggers of the EFL university professors’ anger at the workplace.

As mentioned above, the researchers used the Kolmogorov-Smirnov Test to examine the normality distribution of the collected data. The obtained results are reported in Table 2.

Table 2.

The results of the Kolmogorov-Smirnov Test

Inventory Sub-scales Kolmogorov-Smirnov Z Asymp. Sig. (2-tailed)
LTERI Situation Selection 1.234 0.095
Situation Modification 0.946 0.333
Attention Deployment 0.831 0.495
Reappraisal 0.731 0.660
Suppression 1.352 0.060
Seeking Social Support 1.284 0.074
TSES Student Engagement 0.463 0.983
Instructional Strategies 0.967 0.308
Classroom Management 0.870 0.436
ETS Cognitive Engagement 1.177 0.125
Emotional Engagement 1.339 0.052
Social Engagement: Students 1.216 0.104
Social Engagement: Colleagues 1.275 0.077
TAS Students-related 0.858 0.453
Parents-related 1.181 0.123
Colleagues-related 1.220 0.102
System-related 0.869 0.436
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As reported in Table 2, the collected data were normally distributed because the value of the obtained sigs for the different constructs and their sub-components were larger than the significance level (0.05). Thus, parametric methods for data screening can be applied. As the next step, the researchers employed a Pearson product-moment correlation to inspect the correlations among the participants’ ER, self-efficacy, WE, and anger.

According to Table 3, the correlations among the LTERI and the student engagement (r = 0.657, p < 0.01), the instructional strategies (r = 0.729, p < 0.01), and the classroom management (r = 0.511, p < 0.01) were significant. Regarding the correlations among the LTERI and the teacher engagement, the results yielded cognitive engagement (r = 0.693, p < 0.01), the emotional engagement (r = 0.725, p < 0.01), the social engagement: students (r = 0.530, p < 0.01), and the social engagement: colleagues (r = 0.468, p < 0.01). Furthermore, the correlations among the LTERI and the sub-scales of the participants’ anger were significantly negative as the findings yielded: the students-related (r = -0.508, p < 0.01), the parents-related (r = -0.427, p < 0.05), the colleagues-related (r = -0.448, p < 0.01), and the system-related (r = -0.361, p < 0.05).

Table 3.

The correlation coefficients among the EFL university professors’ ER and self-efficacy, WE, and anger

LTERI student engagement instructional strategies classroom management cognitive engagement emotional engagement social engagement: students social engagement: colleagues students-related parents-related colleagues-related system-related
LTERI 1
student engagement 0.657** 1
instructional strategies 0.729** 0.677** 1
classroom management 0.511** 0.335** 0.659** 1
cognitive engagement 0.693** 0.372** 0.657** 0.585** 1
emotional engagement 0.725** 0.471** 0.227** 0.372** 0.449** 1
social engagement: students 0.530** 0.464** 0.368** 0.390** 0.434** 0.322** 1
social engagement: colleagues 0.468** 0.577** 0.475** 0.411** 0.380** 0.340** 0.745** 1
students-related - 0.508** - 0.513** -0.527** -0.491** -0.476* - 0.544** - 0.461** - 0.584** 1
parents-related - 0.427* - 0.485* - 0.383* -0.542** - 0.441** - 0.361** -0.337** -0.645** 0.507** 1
colleagues-related -0.448** - 0.393* -0.411** -0.255** - 0.292* - 0.252** - 0.307** - 0.509** 0.424** 0.562** 1
system-related - 0.361* - 0.378* -0.259* -0.514** - 0.431* - 0.333** -0.487* - 0.669** 0.548** 0.556** 0.425** 1
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To gauge the structural relations, the researchers used the LISREL 8.80 statistical package to check the suggested model. The following fit indices were utilized to inspect the model fit: the chi-square magnitude, the RMSEA, the GFI, the NFI, and the CFI. As noted by Jöreskog (1990), “the chi-square should be non-significant, the chi-square/df ratio should be lower than 3, and the root mean square error of approximation (RMSEA) should be lower than 0.1” (p. 12). When the cut value is greater than 0.90 for NFI, GFI, and CFI, it indicates a good fit.

As presented in Table 4 (Model 1), the acceptable fit thresholds were reached because the value of chi-square/df ratio was (2.596) and the value of RMSEA was (0.076). Furthermore, as reported, the gained values for GFI (0.932), NFI (0.911), and CFI (0.952) reached the acceptable thresholds.

Table 4.

The results of model fit indices (Model 1)

Fitting indexes χ2 df χ2/df RMSEA GFI NFI CFI
Cut value < 3 < 0.1 > 0.9 > 0.9 > 0.9
The first model 301.14 116 2.596 0.076 0.932 0.911 0.952
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The researchers used the t-values and standardized estimates to inspect the strengths of the causal correlations among the variables. As displayed in Figs. 2 and 3, the participants’ ER significantly contributed to their self-efficacy (β = 0.58, t = 10.92) and WE (β = 0.71, t = 14.74) because the t-value was larger than 1.96. The participants’ ER was negatively correlated with their anger (β = − 0.44, t = -8.32).

Fig. 2.

Fig. 2

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The schematic representation of path coefficient values for the relationship between LTERS, ETS, TSES, and TAS (Model 1)

Fig. 3.

Fig. 3

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T values for path coefficient significance (Model 1)

Table 5 reports the criteria for fit indices in the model 2. The value of the chi-square/df ratio was (2.622) and the value of RMSEA was (0.076) which were found acceptable. The other three fit indices, GFI (0.934), NFI (0.952), and CFI (0.943) reached the acceptable fit thresholds.

Table 5.

The results of model fit indices (Model 2)

Fitting indexes χ2 df χ2/df RMSEA GFI NFI CFI
Cut value < 3 < 0.1 > 0.9 > 0.9 > 0.9
The second model 4767.35 1818 2.622 0.076 0.934 0.952 0.943
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As depicted in Figs. 4 and 5 (Model 2), the university professors’ ER significantly contributed to the all-sub-components of teacher self-efficacy as the findings indicated: the student engagement (β = 0.55, t = 10.40), the instructional strategies (β = 0.61, t = 13.19), the classroom management (β = 0.49, t = 10.15). Additionally, the contributions of the university professors’ ER to the sub-components of their WE were significant. The results indicated that the cognitive engagement (β = 0.56, t = 10.65), the emotional engagement (β = 0.69, t = 13.57), the social engagement: students (β = 0.47, t = 8.67), and the social engagement: colleagues (β = 0.36, t = 6.5). Furthermore, the significantly negative contributions of the university professors’ ER on the sub-components of their anger were revealed. The findings evidenced that the students-related (β = -0.42, t = -8.68), the parents-related (β = -0.31, t = -5.76), the colleagues-related (β = -0.34, t = -5.98), and the system-related (β = -0.28, t = -4.57).

Fig. 4.

Fig. 4

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The schematic representation of path coefficient values for the relationship between LTERS and the sub-components of ETS, TSES, and TAS (Model 2)

Fig. 5.

Fig. 5

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T values for path coefficient significance (Model 2)

Discussion

This research purported to disclose the contributions of EFL university professors’ ER to their self-efficacy, WE, and anger in the Iranian higher education context. The obtained results indicated that the participants’ ER could significantly contribute to their self-efficacy and WE. Additionally, the gained findings uncovered that the participants’ ER contributed negatively to their anger. Therefore, considering the gained findings, the null hypothesis of the present study, claiming that EFL university professors’ emotional regulation does not significantly contribute to their self-efficacy, WE, and anger in the Iranian higher education context was rejected. Given the gained findings of this research, it may be argued that the EFL university professors who cloud regulate their emotions might be able to improve their self-efficacy, engage in work duties, and take control of their anger.

A possible explanation for the obtained findings is that as the EFL university professors might use the ER strategies, they might have been able to manage their emotions effectively and take control of the unpleasant situation their classes. Put it in other words, along with the gained findings, it may be argued that the more EFL university professors might practice emotion regulation, the better they might have been able to modify and manage the emotional obligations. This capacity, in turn, might offer the self-measurement and self-evaluation of the EFL university professors’ emotional experiences and it might have given directions to the improvement of their self-efficacy, the increase of their WE, and the decrease of their anger. A part of the findings evidenced that a strong correlation existed between the EFL university professors’ ER and their self-efficacy. These findings lend support to the results of the previous studies disclosing that there was the intertwined relationship between teachers’ ER and their self-efficacy (Burić et al., 2017; Burić et al., 2020; Burić & Macuka, 2017; Chen & Cheng, 2021; Fan & Wang, 2022). Similarly, Burić and Moè (2020) found interrelationships of teachers’ self-efficacy, pleasant emotions, and well-being, which, in turn, affect their enthusiasm. Furthermore, the gained results are consistent with those of Chen (2018), revealing that teachers’ emotion could be predicted based on their self-efficacy.

The gained results also documented that the EFL university professors’ ER can be a strong predictor of their WE. Considering the obtained findings, it may be argued that, the participants might have used emotion-regulatory strategies to establish a balance in their professional lives. This, in turn, might have acted as a strong motive for the EFL university professors to be more enthusiastic and engaged in their job duties. Furthermore, the findings of this research indicated that ER could maximize the EFL university professors’ social engagement to be more in touch with colleagues and students. That is, ER could be a golden key for raising the EFL university professors’ social commitment and enhance their personal and job accomplishments. Put it differently, in line with the gained results, it may be argued that as the EFL university professors manage their emotions in unpleasant situations, they might have engaged in accomplishing their job duties. These results lend credence to those of the previous studies (e.g., Lazarides & Warner 2020; Topchyan & Woehler, 2020; Zeng et al., 2019), indicating that a strong positive correlation existed between teachers’ ER and WE at the workplace.

Moreover, the gained results evidenced the contributions of EFL university professors’ ER to their anger. In other words, the gained findings indicated that the contributions of the participants’ ER was negative. According to the gained findings, this argument can be made that the more the EFL university professors were armed with the emotion regulatory strategies, the better they might have managed their anger at the workplace. In other words, the results can be attributed to this view that the robust ER strategies might have empowered the EFL university professors to control their expressions of anger. Therefore, one of the overriding influences of ER might have been the efficient handling of job duties by the EFL university professors. Furthermore, given the obtained findings, this argument is made that the EFL university professors with high ER might be inclined toward playing safe and relinquish in the face of challenges and difficulties. The attained findings are in line with those of Namaziandost et al. (2022), revealing that the EFL teachers’ reflective teaching and ER and immunity were positively correlated. Additionally, consistent with the obtained findings, they found that the EFL teachers’ ER was a strong determinant of their immunity. Moreover, the gained results lend credence with those of Li et al. (2022), indicating that the participants’ ER was highly correlated with their critical thinking.

To recap the discussion, the EFL university professors might face diverse stimuli that trigger their feeling of anger at the workplace (i.e., students’ inattention or laziness, students’ misbehaviors, parents’ disrespectful behavior, uncooperative colleagues, (non)attainment of educational objectives, teachers’ burnout, lack of commitment, interference of parents, and dissatisfaction from the administrators to name a few) (Burić & Frenzel, 2019). More specifically, it may be argued that the sources of the participants’ anger might mushroom, especially during the COVID-19 pandemic with its extreme disruption of typical daily life and uncertainty for the future. In such a thorny situation, ER might have enhanced the EFL university professors to navigate the contingencies of the workplace and take control of them. At this time, EFL university professors need to heal the maladaptive anger, and aggression and this can be possible by practicing ER strategies (Burić et al., 2017; Chang & Taxer, 2020).

Conclusion

This research inspected the contributions of ER to EFL university professors’ self-efficacy, WE, and anger. The findings evidenced that ER substantially contributed to the participants’ self-efficacy, WE, and anger. The findings of this research indicated that if university professors, in general and EFL university professors, in particular are to be the backbone of the society and make their students ready for the future they will be able to regulate their emotions. In that case, they can improve their self-efficacy, promote their WE, and relieve their anger at the workplace. According to the gained findings, this conclusion can be made that ER should be considered as a crucial factor in the higher education contexts deserving enough attention.

Some stakeholders may benefit from the implications of the gained findings. First, educational officials of universities can be beneficiary of the gained findings to give particular attention to the psycho-emotional constructs, such as ER among university professors. For example, they can administer some tests to determine if university professors can regulate their emotions efficiently, and if not so, they can hold clinical psychological sessions to ameliorate this problem. Second, teacher-educators may benefit from the obtained findings to incorporate ER in their syllabi to make teacher-students familiar with it in their profession. Last but not least, the obtained results may be beneficial for university professors to be aware of the fact that if they aim to improve their self-efficacy, work-derangement, and anger, they have to regulate their emotions at the workplace.

A range of limitations imposed on this research which can be viewed as points of departure for further research in the future. As this research explored the contributions of EFL university teachers’ ER to their self-efficacy, WE, and anger, further experimental studies are needed to disclose how the instruction of ER strategies may affect EFL university professors’ self-efficacy, WE, and anger. Moreover, since a cross-sectional design was used in this research, a longitudinal design can be implemented to unveil the long-term contributions of ER to university professors’ self-efficacy, WE, and anger. Furthermore, because this research selected its participants from EFL university professors, more studies are needed to explore the contributions of ER to school teachers’ self-efficacy, WE, and anger. Finally, because this research adopted a quantitative design, future studies can use qualitative designs, such as observation and interviews to offer deeper insights into the issue.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Declarations

Ethics approval

Not applicable.

Consent to participate

Informed consent was obtained from all individual participants included in the study.

Informed consent

Not applicable.

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Ehsan Namaziandost, Email: e.namazi75@yahoo.com.

Tahereh Heydarnejad, Email: T.heydarnejad88@yahoo.com.

Vahid Rahmani Doqaruni, Email: rahmani@gonabad.ac.ir.

Zeinab Azizi, Email: zeinab.azizi@abru.ac.ir.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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